Job Description

Company Overview: IRISS, Inc. is a leading innovator in the field of advanced technological solutions, providing cutting-edge products and services to enhance safety, reliability, and efficiency of assets across various industries. Our commitment to pushing boundaries and delivering exceptional solutions has positioned us as a trusted partner for clients seeking top-tier technical expertise in Condition Based Monitoring. IRISS Inc - Leader in Electrical Maintenance Safety Solutions IRISS - YouTube Position: AI Engineer (Conversational Analytics & GenAI Systems) Location: Bengaluru, India About the Product: You will work on IRISS's conversational analytics platform, a GenAI-powered chatbot that transforms natural language queries into validated, compliant, and tenant-aware SQL and visual insights. This platform enables users to ask business questions like ?Show me last month's motor temperature anomalies in Plant 3? and get immediate, accurate dashboards and reports generated safely through AI-driven data pipelines. Our AI stack: - Interprets user intent using LLMs. - Generates validated, policy-compliant SQL. - Executes and visualizes data with context and feedback loops. - Powers a RAG-based (Retrieval-Augmented Generation) framework integrated with existing IoT and analytics microservices Job Overview: You will design, develop, and maintain the AI chatbot platform that serves as the intelligence layer for our SaaS ecosystem. This includes architecting end-to-end conversational pipelines from LLM prompt design to data retrieval, integrating vector- based search systems and RAG pipelines into our service mesh, leveraging AWS AI/ML and orchestration services such as Bedrock, Kendra, OpenSearch, Lambda, ECS, and S3 to build scalable and secure infrastructure, and partnering with full-stack and front-end engineers to embed AI features directly into user workflows Backend: - ASP.NET Core with ABP & ASP.NET Zero modules, EF Core, and SQL Server for tenancy- aware domain logic - Python (FastAPI/Flask) for new microservices and migration targets - APIs: SignalR hubs and REST endpoints exposed through the Web Host - Infrastructure: - AWS Services: ECS for container orchestration, RDS (Aurora) for databases, S3 for storage, Lambda for serverless functions - Hangfire for background jobs, log4net + custom middleware for correlation-aware logging - HealthChecks, Stripe + Firebase integrations - DevOps: AWS CDK-driven Infrastructure as Code with containerized services, Redis caching, and microservice extensions Frontend: - Angular 18 (latest version with standalone components support) - TypeScript 5.5 - RxJS 7.4 for reactive programming - PrimeNG, Angular Material, ngx-charts for UI components Key Responsibilities: - Design and implement backend services in .NET Core (ASP.NET Core Web API) using Entity Framework Core and LINQ - Help migrate our backend APIs to Python microservices architecture - Build clean, testable Angular 18+ UIs and reusable components (standalone) - Design and evolve multi-tenant backend services for assets, sensors, work orders, notifications, and AI workflows - Integrate data sources: SQL (SQL Server/Aurora) and InfluxDB for time-series telemetry - Implement background jobs, rate limiting, and observability using Hangfire, Redis, and log enrichment patterns - Extend REST and SignalR endpoints while maintaining tenant isolation and role-based access control - Collaborate with IoT and data teams to expose sensor data, alerts, reports, and analytics - Implement authentication/authorization, input validation, and error handling across the stack - Participate in code reviews, ADRs, grooming, and release readiness checks - Contribute to CI/CD pipelines (GitHub Actions), basic observability, and performance profiling - Define service boundaries, transactional integrity, and performance within core application layers Core Stack & Technologies AI/ML & Data Intelligence - Python 3.10+ (FastAPI, LangChain, Haystack, or equivalent) - LLMs: OpenAI, Anthropic, Hugging Face, or open-source models (LLaMA, Mistral, Falcon) - RAG Systems: FAISS, Pinecone, OpenSearch Vector Store, or ChromaDB - Prompt Orchestration: LangChain, Semantic Kernel, or internal tooling - Data Validation & Safety: SQL sanitization layers and policy enforcement modules - Visualization Layer: Chart.js or D3.js integration for generated insights Cloud & Infrastructure: - AWS Bedrock, Kendra, OpenSearch, Lambda, S3, CloudWatch, ECS, and EC2 - API Gateway for AI microservices - Redis or DynamoDB for caching and conversation state - OpenTelemetry for observability - CI/CD using GitHub Actions, AWS CDK, and Docker-based microservices Front-End & Integration - Works closely with Angular 18+ applications and .NET/Python backend microservices - Exposes APIs to the Full-Stack and Front-End teams for seamless user interactions - Implements real-time feedback mechanisms for model evaluation and tuning Key Responsibilities: - Architect, develop, and maintain the GenAI chatbot platform from the ground up - Build multi-turn conversation flows and contextual memory for data queries - Implement RAG pipelines using vector databases and curated embeddings - Integrate open-source and commercial LLMs through APIs or local deployment - Create safety and compliance modules that validate SQL and policy rules before execution - Collaborate with backend engineers to design AI microservices that scale horizontally - Deploy, monitor, and optimize models using AWS Bedrock, Kendra, and OpenSearch - Maintain observability and feedback loops for improving model accuracy and reliability - Partner with front-end teams to deliver chat-first analytics interfaces - Contribute to documentation, testing, and architectural decision records for AI systems Requirements: - Bachelor's or Master's degree in Computer Science, Data Science, or a related field - Minimum 3 years of experience developing and deploying AI-powered applications or chatbots - Strong Python expertise (FastAPI, Flask, or Django for microservices) - Experience with LLM integration (OpenAI, Bedrock, Hugging Face, or local models) - Hands-on experience with AWS ecosystem including Bedrock, Kendra, OpenSearch, ECS, Lambda, and CloudWatch - Deep understanding of RAG architecture, vector databases, and embeddings-based retrieval - Knowledge of prompt design, model orchestration, and AI safety validation - Familiarity with SQL and multi-tenant data systems - Experience with Docker, Git-based CI/CD, and microservice architectures Nice-to-Have - Experience fine-tuning or hosting open-source LLMs (LLaMA, Mistral, Falcon) - Understanding of LangChain Agents or Semantic Kernel pipelines - Familiarity with Angular and .NET ecosystems for end-to-end integration - Exposure to observability frameworks such as OpenTelemetry, Prometheus, or Grafana - Knowledge of enterprise data governance and AI compliance frameworks - Contributions to open-source AI projects or custom LLM integrations What You'll Work On: - Migration of .NET Core backend services to Python microservices - Tenant-aware APIs powering asset hierarchies, predictive maintenance, and automated work orders - Real-time dashboards and notifications for sensor events, alerts, and chat integration - Performance and reliability for data-heavy dashboards (pagination, caching, change detection) - Background workflows orchestrating AI-driven insights and report exports - REST services consumed by Angular dashboards and mobile clients - Observability hooks (health checks, telemetry, correlation IDs) for enterprise-grade reliability - Developer experience improvements (codegen, linting, templates, better local envs) What You Will Build: - A conversational analytics chatbot capable of generating real-time, compliant SQL queries - RAG pipelines that fetch and embed domain knowledge across tenants - Context-aware AI microservices integrated with IRISS?s monitoring and reporting systems - Evaluation dashboards for prompt performance, latency, and query accuracy - Continuous learning and feedback loops to improve the GenAI system over time Development Environment - Python 3.10+, FastAPI, LangChain - AWS Bedrock, OpenSearch, Kendra, Lambda, ECS - Angular 18+ for embedded UIs - Node.js 16+, Yarn, VS Code - GitHub Actions and AWS CDK for CI/CD - Dockerized microservices architecture Compensation: Competitive salary, benefits, and strong growth opportunities.